Here, \(X\)  represents the sample that is drawn from a uniform distribution over the hyperparameter space \(\Lambda \) , while \(Y\)  is the sample generated by the BO process. The kernel \(k\)  is chosen to be the radial basis function kernel with parameter \(\sigma \)  being set to the median L2-distance between sample points. This heuristic is commonly used [1]}.
